Field of system identification have become important discipline. Identification is basically the process of developing or improving a mathematical representation of a physical system using experimental data. The artificial neural network is a newly developed technique among the identification methods. Dynamic function mapping, including the structural dynamic model is still a challenging topic ...

Computer interfaces provide an environment that allows for multiple objectively optimal solutions but individuals will, over time, use a smaller number of subjectively optimal solutions, developed as habits that have been formed and tuned by repetition. Designing an interface agent to provide assistance in this environment thus requires not only knowledge of the objectively optimal solutions, b...

We present a novel algorithm for reconstructing the topology of regulatory networks based on the Stochastic Logical Network model. Our method, by avoiding the computation of the Markov model parameters is able to reconstruct the topology of the SLN model in polynomial time instead of exponential as in previous study [29]. To test the performance of the method, we apply it to different datasets ...

This paper presents a novel approach to simulation metamodeling using dynamic Bayesian networks (DBNs) in the context of discrete event simulation. A DBN is a probabilistic model that represents the joint distribution of a sequence of random variables and enables the efficient calculation of their marginal and conditional distributions. In this paper, the construction of a DBN based on simulati...

Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any model that is learnt from the data will average over the different dependency structures. Paradigms that try to explain underlying processes and observed events in multivariate time series must explicitly model these changes in ord...

This paper addresses modeling user behavior in interactions between two people who do not share a common spoken language and communicate with the aid of an automated bidirectional speech translation system. These interaction settings are complex. The translation machine attempts to bridge the language gap by mediating the verbal communication, noting however that the technology may not be alway...

The situation of information security is difficult to be precise, autonomous and controllable. In this situation, the situation of the system is based on Fuzzy Dynamic Bayesian network. The model of situation awareness and situation estimation is constructed. The simulation results are compared with that of static Bayesian network model. The experimental results show that this method can better...

In this paper, we propose a new method for recognizing hand gestures in a continuous video stream using a dynamic Bayesian network or DBN model. The proposed method of DBN-based inference is preceded by steps of skin extraction and modelling, and motion tracking. Then we develop a gesture model for oneor two-hand gestures. They are used to define a cyclic gesture network for modeling continuous...

The exponential rise in wireless communication demands and allied applications have revitalized academia-industries to develop more efficient routing protocols. Wireless Sensor Network (WSN) being battery operated network, it often undergoes node death-causing pre-ma...